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Identification of inter-individual and gene-specific variances in mRNA expression profiles in the RA SM

ABSTRACT: Background. Rheumatoid arthritis (RA) is a chronic inflammatory and destructive joint disease, characterized by overexpression of pro-inflammatory/-destructive genes and other activating genes (e.g., proto-oncogenes) in the synovial membrane (SM). The gene expression in disease is often characterized by significant inter-individual variances via specific synchronization/ desynchronization of gene expression. To elucidate the contribution of the variance to the pathogenesis of disease, expression variances were tested in SM samples of RA patients, osteoarthritis (OA) patients, and normal controls (NC). Results. For the comparison between RA and NC, 568 genes with significantly different variances in the 2 groups (p < 0.05; Bonferroni/Holm corrected Brown-Forsythe version of the Levene-Test) were selected. For the comparison between RA and OA, 333 genes were selected. Using the Kyoto encyclopedia of genes and genomes (KEGG), 10 pathways/complexes significantly affected by higher gene expression variances were identified in RA compared to NC, including cytokine – cytokine receptor interactions, the TGF-pathway, and anti-apoptosis. Compared to OA, 3 pathways with significantly higher variances were identified in RA (e.g., B cell receptor signaling, VEGF signaling). Functionally, the majority of the identified pathways is involved in the regulation of inflammation, proliferation, cell survival, and angiogenesis. Conclusion. In RA, a number of disease-relevant or even disease-specific pathways/complexes are characterized by broad intra-group, inter-individual expression variances. This indicates that RA pathogenesis in different individuals may depend to a lesser extent on common alterations of the expression of specific key genes, but on individual-specific alterations of different genes resulting in common disturbances of key pathways.

ORGANISM(S): Homo sapiens

PROVIDER: GSE12021 | GEO | 2008/09/02

SECONDARY ACCESSION(S): PRJNA113297

REPOSITORIES: GEO

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Project description:Background. Rheumatoid arthritis (RA) is a chronic inflammatory and destructive joint disease, characterized by overexpression of pro-inflammatory/-destructive genes and other activating genes (e.g., proto-oncogenes) in the synovial membrane (SM). The gene expression in disease is often characterized by significant inter-individual variances via specific synchronization/ desynchronization of gene expression. To elucidate the contribution of the variance to the pathogenesis of disease, expression variances were tested in SM samples of RA patients, osteoarthritis (OA) patients, and normal controls (NC). Results. For the comparison between RA and NC, 568 genes with significantly different variances in the 2 groups (p < 0.05; Bonferroni/Holm corrected Brown-Forsythe version of the Levene-Test) were selected. For the comparison between RA and OA, 333 genes were selected. Using the Kyoto encyclopedia of genes and genomes (KEGG), 10 pathways/complexes significantly affected by higher gene expression variances were identified in RA compared to NC, including cytokine â cytokine receptor interactions, the TGF-pathway, and anti-apoptosis. Compared to OA, 3 pathways with significantly higher variances were identified in RA (e.g., B cell receptor signaling, VEGF signaling). Functionally, the majority of the identified pathways is involved in the regulation of inflammation, proliferation, cell survival, and angiogenesis. Conclusion. In RA, a number of disease-relevant or even disease-specific pathways/complexes are characterized by broad intra-group, inter-individual expression variances. This indicates that RA pathogenesis in different individuals may depend to a lesser extent on common alterations of the expression of specific key genes, but on individual-specific alterations of different genes resulting in common disturbances of key pathways. Experiment Overall Design: Expression variances were tested in synovial membrane samples of rheumatoid arthritis patients, osteoarthritis patients, and normal controls (see publication for further details).

Project description:Rheumatoid synoviocytes, which consist of fibroblast-like synoviocytes (FLS) and synovial macrophages (SM), are crucial for the progression of rheumatoid arthritis (RA). Particularly, FLS of RA patients (RA-FLS) exhibit invasive characteristics reminiscent of cancer cells, destroying cartilage and bone, although it remains unresolved how RA-FLS exhibit invasive phenotype. RA-FLS and SM originate differently from mesenchymal and myeloid cells, respectively, but share many pathologic functions. However, the molecular signatures and biological networks representing the distinct and shared features of the two cell types are unknown. Presently, we performed global transcriptome profiling of FLS and SM obtained from RA and osteoarthritis patients. By comparing the transcriptomes, we identified distinct molecular signatures and cellular processes defining invasiveness of RA-FLS and pro-inflammatory properties of RA synovial macrophages (RA-SM), respectively. Interestingly, under interleukin1β-stimulated condition, RA-FLS newly acquired pro-inflammatory signature mimicking RA-SM without losing invasive properties. We next reconstructed a network model that delineates the shared, RA-FLS-dominant (invasive), and RA-SM-dominant (inflammatory) processes. From the network model, we selected 13 genes, including POSTN and TWIST1, as novel regulator candidates responsible for FLS invasiveness. Of note, POSTN and TWIST1 expressions were elevated in independent RA-FLS and were further instigated by interleukin1β. In vitro functional assays demonstrated the requirement of POSTN and TWIST1 for migration and invasion of RA-FLS stimulated with interleukin1β. Taken together, our systems approach to rheumatoid synovitis provides a basis for identifying novel regulators responsible for pathological features of RA-FLS and RA-SM, demonstrating how a certain type of cells acquires functional redundancy under chronic inflammatory conditions. To identify molecular signatures of FLS and MLS in RA joints, we isolated FLS from synovial tissues of RA and osteoarthritis (OA) patients, obtained synovial macrophages from synovial fluid of RA patients, and differentiated control macrophages from peripheral blood of healthy subjects. Also, we stimulated FLS with IL1β, and then analyzed gene expression profiles of both IL1β-stimulated RA-FLS and OA-FLS

Project description:Objectives: Epigenetics can influence disease susceptibility and severity. While DNA methylation of individual genes has been explored in autoimmunity, no unbiased systematic analyses have been reported. Therefore, a genome-wide evaluation of DNA methylation loci in fibroblast-like synoviocytes (FLS) isolated from the site of disease in rheumatoid arthritis (RA) was performed. Methods: Genomic DNA was isolated from six RA and five osteoarthritis (OA) FLS lines and evaluated using the Illumina HumanMethylation450 chip. Cluster analysis of data was performed and corrected using Benjamini–Hochberg adjustment for multiple comparisons. Methylation was confirmed by pyrosequencing and gene expression was determined by qPCR. Pathway analysis was performed using the Kyoto Encyclopedia of Genes and Genomes. Results: RA and control FLS segregated based on DNA methylation, with 1859 differentially methylated loci. Hypomethylated loci were identified in key genes relevant to RA, such as CHI3L1, CASP1, STAT3, MAP3K5, MEFV and WISP3. Hypermethylation was also observed, including TGFBR2 and FOXO1. Hypomethylation of individual genes was associated with increased gene expression. Grouped analysis identified 207 hypermethylated or hypomethylated genes with multiple differentially methylated loci, including COL1A1, MEFV and TNF. Hypomethylation was increased in multiple pathways related to cell migration, including focal adhesion, cell adhesion, transendothelial migration and extracellular matrix interactions. Confirmatory studies with OA and normal FLS also demonstrated segregation of RA from control FLS based on methylation pattern. Conclusions: Differentially methylated genes could alter FLS gene expression and contribute to the pathogenesis of RA. DNA methylation of critical genes suggests that RA FLS are imprinted and implicate epigenetic contributions to inflammatory arthritis. Fibroblast-like synoviocyte cell-lines from osteoarthritis (OA) and rheumatoid arthritis (RA) patients.

Project description:Discrimination of rheumatoid arthritis (RA) patients from patients with other inflammatory/degenerative joint diseases or healthy individuals purely on the basis of genes differentially expressed in high-throughput data has proven very difficult. Thus, the present study sought to achieve such discrimination by employing a novel unbiased approach using rule-based classifiers. Three multi-center genome-wide transcriptomic data sets (Affymetrix HG- U133 A/B) from a total of 79 individuals, including 20 healthy controls (control group - CG), as well as 26 osteoarthritis (OA) and 33 RA patients, were used to infer rule- based classifiers to discriminate the disease groups. The rules were ranked with respect to Kiendl’s statistical relevance index, and the resulting rule set was optimized by pruning. The rule sets were inferred separately from data of one of three centers and applied to the two remaining centers for validation. All rules from the optimized rule sets of all centers were used to analyze their biological relevance applying the software Pathway Studio. The optimized rule sets for the three centers contained a total of 29, 20, and 8 rules (including 10, 8, and 4 rules for ‘RA’), respectively. The mean sensitivity for the prediction of RA based on six center-to-center tests was 96% (range 90% to 100%), that for OA 86% (range 40% to 100%). The mean specificity for RA prediction was 94% (range 80% to 100%), that for OA 96% (range 83.3% to 100%). The average overall accuracy of the three different rule-based classifiers was 91% (range 80% to 100%). Unbiased analyses by Pathway Studio of the gene sets obtained by discrimination of RA from OA and CG with rule-based classifiers resulted in the identification of the pathogenetically and/or therapeutically relevant interferon-gamma and GM-CSF pathways. First-time application of rule-based classifiers for the discrimination of RA resulted in high performance, with means for all assessment parameters close to or higher than 90%. In addition, this unbiased, new approach resulted in the identification not only of pathways known to be critical to RA, but also of novel molecules such as serine/threonine kinase 10. Synovial tisssue from healthy joints, OA joints, and RA joints.

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Identification of inter-individual and gene-specific variances in mRNA expression profiles in the RA SM

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